Multimode Process Monitoring Based on Density Space Clustering Locally Linear Embedding Technique-Reference-Cited by-同舟云学术

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Multimode Process Monitoring Based on Density Space Clustering Locally Linear Embedding Technique

Published:2023-07-14 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd Conference on Fully Actuated System Theory and Applications (CFASTA)
language:
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Author:

Feng LiWei¹,Ai Hao²,Li Yuan³

Affiliation:

1. Shenyang University of Chemical Technology,College of Science,Shenyang,110142

2. Shenyang University of Chemical Technology,College of Computer Science and Technology,Shenyang,110142

3. Shenyang University of Chemical Technology,College of Information Engineering,Shenyang,Liaoning,110142

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10243163/10243123/10243375.pdf?arnumber=10243375

Reference20 articles.

1. Nonlinear Dynamic Process Monitoring Based on Two-Step Dynamic Local Kernel Principal Component Analysis

2. Nonlinear Multimode Industrial Process Fault Detection Using Modified Kernel Principal Component Analysis

3. Fault Detection Based on Modified Kernel Semi-Supervised Locally Linear Embedding

4. Nonlinear Dimensionality Reduction by Locally Linear Embedding

5. Fault diagnosis with multivariate statistical models part I: using steady state fault signatures

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